Analyzing data sets of billions of records has now become a regular task in many companies and institutions. In the statistical analysis of those massive data sets, sampling generally plays a very important role. In this work, we describe a scalable simple random sampling algorithm, named ScaSRS, which uses probabilistic thresholds to decide on the fly whether to accept, reject, or wait-list an...

We present a sampling method called, CacheDiff, that has both time and space complexity of O(k) to randomly select k items from a pool of N items, in which N is known.

In Experiment 1, subjects estimated {1) the mean of a random sample of 10 scores consisting of 9 unknown scores and 1 known score that was divergent from the population mean and {2} the mean of the 9 unknown scores. The modal answer {about 40% of the responses} for both sample means was the population mean. The results extend the work of Tversky and Kahneman {1971} by demonstrating that subject...

Random sampling is a classical tool in constrained optimization. Under favorable conditions, the optimal solution subject to a small subset of randomly chosen constraints violates only a small subset of the remaining constraints. Here we study the following variant that we call random sampling with removal: suppose that after sampling the subset, we remove a fixed number of constraints from the...

1 EE Dept., The Pennsylvania State University. University Park, PA 16802, USA, [email protected] 2 EE Dept., The Pennsylvania State University. University Park, PA 16802, USA, [email protected] 3 EE Dept., The Pennsylvania State University. University Park, PA 16802, USA, [email protected] 4 EE Dept., The Pennsylvania State University. University Park, PA 16802, USA, [email protected]....

Random Sampling from Databases by Frank Olken Doctor of Philosophy in Computer Science University of California at Berkeley Professor Michael Stonebraker, Chair In this thesis I describe e cient methods of answering random sampling queries of relational databases, i.e., retrieving random samples of the results of relational queries. I begin with a discussion of the motivation for including samp...